Mass Spectrometric Analysis of Exhaled Breath for the Identification of Volatile Organic Compound Biomarkers in Esophageal and Gastric Adenocarcinoma.

OBJECTIVE: The present study assessed whether exhaled breath analysis using Selected Ion Flow Tube Mass Spectrometry could distinguish esophageal and gastric adenocarcinoma from noncancer controls. BACKGROUND: The majority of patients with upper gastrointestinal cancer present with advanced disease, resulting in poor long-term survival rates. Novel methods are needed to diagnose potentially curable upper gastrointestinal malignancies. METHODS: A Profile-3 Selected Ion Flow Tube Mass Spectrometry instrument was used for analysis of volatile organic compounds (VOCs) within exhaled breath samples. All study participants had undergone upper gastrointestinal endoscopy on the day of breath sampling. Receiver operating characteristic analysis and a diagnostic risk prediction model were used to assess the discriminatory accuracy of the identified VOCs. RESULTS: Exhaled breath samples were analyzed from 81 patients with esophageal (N = 48) or gastric adenocarcinoma (N = 33) and 129 controls including Barrett's metaplasia (N = 16), benign upper gastrointestinal diseases (N = 62), or a normal upper gastrointestinal tract (N = 51). Twelve VOCs-pentanoic acid, hexanoic acid, phenol, methyl phenol, ethyl phenol, butanal, pentanal, hexanal, heptanal, octanal, nonanal, and decanal-were present at significantly higher concentrations (P < 0.05) in the cancer groups than in the noncancer controls. The area under the ROC curve using these significant VOCs to discriminate esophageal and gastric adenocarcinoma from those with normal upper gastrointestinal tracts was 0.97 and 0.98, respectively. The area under the ROC curve for the model and validation subsets of the diagnostic prediction model was 0.92 ±â€Š0.01 and 0.87 ±â€Š0.03, respectively. CONCLUSIONS: Distinct exhaled breath VOC profiles can distinguish patients with esophageal and gastric adenocarcinoma from noncancer controls.

In vivo endoscopic tissue identification by rapid evaporative ionization mass spectrometry (REIMS).

Gastrointestinal cancers are a leading cause of mortality, accounting for 23 % of cancer-related deaths worldwide. In order to improve outcomes from these cancers, novel tissue characterization methods are needed to facilitate accurate diagnosis. Rapid evaporative ionization mass spectrometry (REIMS) is a technique developed for the in vivo classification of human tissue through mass spectrometric analysis of aerosols released during electrosurgical dissection. This ionization technique was further developed by utilizing surface induced dissociation and was integrated with an endoscopic polypectomy snare to allow in vivo analysis of the gastrointestinal tract. We tested the classification performance of this novel endoscopic REIMS method in vivo. It was shown to be capable of differentiating between healthy layers of the intestinal wall, cancer, and adenomatous polyps based on the REIMS fingerprint of each tissue type in vivo.

Selected ion flow tube mass spectrometry analysis of volatile metabolites in urine headspace for the profiling of gastro-esophageal cancer.

Urine is considered an ideal biofluid for clinical investigation because it is obtained noninvasively and relatively large volumes are easily acquired. In this study, selected ion flow tube mass spectrometry (SIFT-MS) has been applied for the quantification of volatile organic compounds (VOCs) in the headspace vapor of urine samples, which were retrieved from three groups of patients with gastro-esophageal cancer, noncancer diseases of the upper gastro-intestinal tract, and a healthy cohort. Eleven VOCs have been investigated in this study. The concentrations of seven VOCs-acetaldehyde, acetone, acetic acid, hexanoic acid, hydrogen sulfide, methanol, and phenol-were found to be significantly different between cancer, positive control, and healthy groups using the Kruskal-Wallis test. The concentrations of acetaldehyde, acetone, acetic acid, hexanoic acid, hydrogen sulfide, and methanol were increased in the cancer cohort compared with healthy controls while the concentration of phenol decreased. The differences in the concentrations of ethanol, propanol, methyl phenol, and ethyl phenol were not significant between cancer and control groups. Receiver operating characteristics (ROC) analysis was applied for a combination of six VOCs (acetaldehyde, acetone, acetic acid, hexanoic acid, hydrogen sulfide, and methanol) to discriminate cancer patients from noncancer controls. The integrated area under ROC curve is 0.904. This result indicates that VOC profiling may be suitable in identifying those at high risk of gastro-esophageal cancer. Therefore, further investigations should be undertaken to assess the potential for VOC profiling as a new screening test in gastro-esophageal cancer.

Selected ion flow tube mass spectrometry analysis of exhaled breath for volatile organic compound profiling of esophago-gastric cancer.

Exhaled breath analysis of volatile organic compounds (VOCs) has great potential in terms of disease diagnosis and measuring physiological response to treatment. In this study, selected ion flow tube mass spectrometry (SIFT-MS) has been applied for the quantification of VOCs in the exhaled breath from 3 groups of patients, viz., those with esophago-gastric cancer, noncancer diseases of the upper gastro-intestinal tract, and a healthy upper gastrointestinal tract cohort. A total of 17 VOCs have been investigated in this study. The concentrations of 4 VOCs, hexanoic acid, phenol, methyl phenol, and ethyl phenol, were found to be significantly different between cancer and positive control groups using the Mann-Whitney U test. Receiver operating characteristics (ROC) analysis was applied for a combination of 4 VOCs (hexanoic acid, phenol, methyl phenol, and ethyl phenol) to discriminate the esophago-gastric cancer cohort from positive controls. The integrated area under the ROC curve (AUC) is 0.91. The results highlight the potential of VOC profiling as a noninvasive test to identify those with esophago-gastric cancer.

Selected ion flow tube-MS analysis of headspace vapor from gastric content for the diagnosis of gastro-esophageal cancer.

Gastric content is a complex biofluid within the human stomach which has an important role in digestive processes. It is believed that gastric content may be a contributory factor in the development of upper gastro-intestinal diseases. In this work, selected ion flow tube mass spectrometry (SIFT-MS) has been applied to the quantification of volatile organic compounds (VOCs) in the headspace vapor of gastric content samples, which were retrieved from three groups of patients, including those with gastro-esophageal cancer, noncancer diseases of the upper gastro-intestinal tract, and a healthy cohort. Twelve VOCs have been investigated in this study; the following 7 VOCs, acetone, formaldehyde, acetaldehyde, hexanoic acid, hydrogen sulphide, hydrogen cyanide, and methyl phenol, were found to be significantly different between cancer and healthy groups by the Mann-Whitney U test. Receiver operating characteristics (ROC) analysis was applied for the combined VOCs of acetaldehyde, formaldehyde, hydrogen sulphide, and methyl phenol to discriminate cancer patients from healthy controls. The area under the curve (AUC) was 0.9. This result raises the prospect that a VOC profile rather than a single biomarker may be preferable in the molecular-orientated diagnosis of gastro-oseophageal cancer, and this warrants further investigation to assess its potential application as a new diagnostic test.

De Novo Lipogenesis Alters the Phospholipidome of Esophageal Adenocarcinoma.

The incidence of esophageal adenocarcinoma is rising, survival remains poor, and new tools to improve early diagnosis and precise treatment are needed. Cancer phospholipidomes quantified with mass spectrometry imaging (MSI) can support objective diagnosis in minutes using a routine frozen tissue section. However, whether MSI can objectively identify primary esophageal adenocarcinoma is currently unknown and represents a significant challenge, as this microenvironment is complex with phenotypically similar tissue-types. Here, we used desorption electrospray ionization-MSI (DESI-MSI) and bespoke chemometrics to assess the phospholipidomes of esophageal adenocarcinoma and relevant control tissues. Multivariate models derived from phospholipid profiles of 117 patients were highly discriminant for esophageal adenocarcinoma both in discovery (AUC = 0.97) and validation cohorts (AUC = 1). Among many other changes, esophageal adenocarcinoma samples were markedly enriched for polyunsaturated phosphatidylglycerols with longer acyl chains, with stepwise enrichment in premalignant tissues. Expression of fatty acid and glycerophospholipid synthesis genes was significantly upregulated, and characteristics of fatty acid acyls matched glycerophospholipid acyls. Mechanistically, silencing the carbon switch ACLY in esophageal adenocarcinoma cells shortened glycerophospholipid chains, linking de novo lipogenesis to the phospholipidome. Thus, DESI-MSI can objectively identify invasive esophageal adenocarcinoma from a number of premalignant tissues and unveils mechanisms of phospholipidomic reprogramming. SIGNIFICANCE: These results call for accelerated diagnosis studies using DESI-MSI in the upper gastrointestinal endoscopy suite, as well as functional studies to determine how polyunsaturated phosphatidylglycerols contribute to esophageal carcinogenesis.

A Comparison of DESI-MS and LC-MS for the Lipidomic Profiling of Human Cancer Tissue.

In this study, we make a direct comparison between desorption electrospray ionization-mass spectrometry (DESI-MS) and ultraperformance liquid chromatography-electrospray ionization-mass spectrometry (UPLC-ESI-MS) platforms for the profiling of glycerophospholipid (GPL) species in esophageal cancer tissue. In particular, we studied the similarities and differences in the range of GPLs detected and the congruency of their relative abundances as detected by each analytical platform. The main differences between mass spectra of the two modalities were found to be associated with the variance in adduct formation of common GPLs, rather than the presence of different GPL species. Phosphatidylcholines as formate adducts in UPLC-ESI-MS accounted for the majority of differences in negative ion mode and alkali metal adducts of phosphatidylcholines in DESI-MS for positive ion mode. Comparison of the relative abundance of GPLs, normalized to a common peak, revealed a correlation coefficient of 0.70 (P < 0.001). The GPL profile detected by DESI-MS is congruent to UPLC-ESI-MS, which reaffirms the role of DESI-MS for lipidomic profiling and a potential premise for quantification.

Imaging of Esophageal Lymph Node Metastases by Desorption Electrospray Ionization Mass Spectrometry.

Histopathological assessment of lymph node metastases (LNM) depends on subjective analysis of cellular morphology with inter-/intraobserver variability. In this study, LNM from esophageal adenocarcinoma was objectively detected using desorption electrospray ionization-mass spectrometry imaging (DESI-MSI). Ninety lymph nodes (LN) and their primary tumor biopsies from 11 esophago-gastrectomy specimens were examined and analyzed by DESI-MSI. Images from mass spectrometry and corresponding histology were coregistered and analyzed using multivariate statistical tools. The MSIs revealed consistent lipidomic profiles of individual tissue types found within LNs. Spatial mapping of the profiles showed identical distribution patterns as per the tissue types in matched IHC images. Lipidomic profile comparisons of LNM versus the primary tumor revealed a close association in contrast to benign LN tissue types. This similarity was used for the objective prediction of LNM in mass spectrometry images utilizing the average lipidomic profile of esophageal adenocarcinoma. The multivariate statistical algorithm developed for LNM identification demonstrated a sensitivity, specificity, positive predictive value, and negative predictive value of 89.5%, 100%, 100%, and 97.2%, respectively, when compared with gold-standard IHC. DESI-MSI has the potential to be a diagnostic tool for perioperative identification of LNM and compares favorably with techniques currently used by histopathology experts. Cancer Res; 76(19); 5647-56. ©2016 AACR.

Analysis of Exhaled Breath Volatile Organic Compounds in Inflammatory Bowel Disease: A Pilot Study.

BACKGROUND AND AIMS: Distinguishing between the inflammatory bowel diseases [IBD], Crohn's disease [CD] and ulcerative colitis [UC], is important for determining management and prognosis. Selected ion flow tube mass spectrometry [SIFT-MS] may be used to analyse volatile organic compounds [VOCs] in exhaled breath: these may be altered in disease states, and distinguishing breath VOC profiles can be identified. The aim of this pilot study was to identify, quantify, and analyse VOCs present in the breath of IBD patients and controls, potentially providing insights into disease pathogenesis and complementing current diagnostic algorithms. METHODS: SIFT-MS breath profiling of 56 individuals [20 UC, 18 CD, and 18 healthy controls] was undertaken. Multivariate analysis included principal components analysis and partial least squares discriminant analysis with orthogonal signal correction [OSC-PLS-DA]. Receiver operating characteristic [ROC] analysis was performed for each comparative analysis using statistically significant VOCs. RESULTS: OSC-PLS-DA modelling was able to distinguish both CD and UC from healthy controls and from one other with good sensitivity and specificity. ROC analysis using combinations of statistically significant VOCs [dimethyl sulphide, hydrogen sulphide, hydrogen cyanide, ammonia, butanal, and nonanal] gave integrated areas under the curve of 0.86 [CD vs healthy controls], 0.74 [UC vs healthy controls], and 0.83 [CD vs UC]. CONCLUSIONS: Exhaled breath VOC profiling was able to distinguish IBD patients from controls, as well as to separate UC from CD, using both multivariate and univariate statistical techniques.

Investigation of C3-C10 aldehydes in the exhaled breath of healthy subjects using selected ion flow tube-mass spectrometry (SIFT-MS).

Aldehydes have attracted great scientific and clinical interest as potential disease biomarkers. We have investigated selected ion flow tube-mass spectrometry (SIFT-MS) in detecting and quantifying C3 to C10 saturated aldehydes (propanal, butanal, pentanal, hexanal, heptanal, octanal, nonanal and decanal) from the exhaled breath of 26 healthy human volunteers. To assess the reliability of the Nalophan® bag sampling method employed, the water level in the breath sample was measured up to 4 h after collection and showed no significant degradation. Propanal was found to be the most abundant aldehyde in the exhaled breath of healthy volunteers. For the C4-C10 aldehydes, their median concentrations were all less than 3 ppbv, demonstrating only trace quantities are present in the exhaled breath of the 26 healthy volunteers.

Simultaneous readout of multiple microcantilever arrays with phase-shifting interferometric microscopy.

A complete system for the simultaneous monitoring of multiple cantilever sensors from different sensor arrays has been developed and tested for gas- and liquid-phase applications. The cantilever sensors are operated in static-deflection mode and the readout is achieved with phase-shifting interferometric microscopy (PSIM). In contrast to existing cantilever-sensor readout methods, PSIM is not dependent on alignment and allows the monitoring of the entire displacement profiles of all cantilevers within the field of view, using just one light source. To complement the PSIM readout, we have developed a sample cell, which can hold multiple cantilever-array chips, allows for very fast and reproducible sensor-chip replacement, has very low sample-volume requirements, and allows for individual or common addressing of all chips in the sample cell. We demonstrate the functionality of our microcantilever sensor system with a setup that can monitor eight cantilevers from four different sensor chips simultaneously.